Analysis of equilibrium-oriented bidding strategies with inaccurate electricity market models

In order to make competitive electricity markets effective, bidding generation companies (GENCOs) need to estimate market demand models according to information available to each of them. However, many stochastic factors (e.g. weather, demand side features) make it very hard for GENCOs to accurately capture the actual market demand in a model. Each GENCO might hold an estimated model deviating, from the real market model as well as from its peers’. Little work has been done in discussing the impacts of model deviations towards the design of GENCO’s bidding strategies.In this paper, the effects of model deviations upon the equilibrium-oriented bidding methods (EOBMs), more specifically conjectural variation (CV) based methods, are studied. We relax the strong assumptions that one uniform and accurate market demand model is employed by all GENCOs in the basic CV-based learning bidding algorithm (CVBA). In this work, the market demand model utilized for bidding by each GENCO is different from each other and from the actual market model as well. The impacts of such model deviations are analyzed from both theoretical and simulation perspective. Theoretical analyses point out that as a consequence of the model deviations it is possible that the basic CVBA algorithm will bring the bidding process into an unstable state. In order to eliminate the effects from inaccurate modeling, a CV-based learning bidding method with data filtering capabilities is proposed. Several sets of simulations have been done to test the impact of the model deviations. The simulation results confirm the theoretical analyses. The feasibility and effectiveness of the proposed bidding methods are also verified. The proposed algorithm can bring systems into stable state even when model deviations exist.     

GENCO's Risk-Based Maintenance Outage Scheduling

This paper presents a stochastic model for the optimal risk-based generation maintenance outage scheduling based on hourly price-based unit commitment in a generation company (GENCO). Such maintenance outage schedules will be submitted by GENCOs to the ISO for approval before implementation. The objective of a GENCO is to consider financial risks when scheduling its midterm maintenance outages. The GENCO also coordinates its proposed outage scheduling with short-term unit commitment for maximizing payoffs. The proposed model is a stochastic mixed integer linear program in which random hourly prices of energy, ancillary services, and fuel are modeled as scenarios in the Monte Carlo method. Financial risks associated with price uncertainty are considered by applying expected downside risks which are incorporated explicitly as constraints. This paper shows that GENCOs could decrease financial risks by adjusting expected payoffs. Illustrative examples show the calculation of GENCO's midterm generation maintenance schedule, risk level, hourly unit commitment, and hourly dispatch for bidding into energy and ancillary services markets.     

市场环境下发电厂商机组检修新策略

提出市场环境下基于单台机组弹性检修模型的发电厂商(generating company,GENCO)机组检修新策略。针对单台机组多出力运行状态,提出评估检修与否的两个经济指标：检修经济损失值Loss和运行风险损失值Loss,P,前者反映了机组检修时的经济损失,后者反映了继续运行时由于故障造成的风险损失,通过比较两者,便可确定单台机组的最优检修时段及可检修区间。根据该发电厂商中各机组的预期经济损失ELoss值确定其规划检修顺序,在单台机组的弹性检修模型基础上,依次确定各机组的检修时段。在该策略下,各机组不再按传统的固定时间间隔进行检修,确保了其安全经济运行,体现了发电厂商的市场主体地位。最后,用一个简单算例说明了该策略的合理性与有效性。     

Binary fireworks algorithm for profit based unit commitment (PBUC) problem

The deregulation of electricity markets has transformed the unit commitment and economic dispatch problem in power systems from cost minimization approach to profit maximization approach in which generation company (GENCO)/independent power producer (IPP) would schedule the available generators to maximize the profit for the forecasted prices in day ahead market (DAM). The PBUC is a highly complex optimization problem with equal, in equal and bound constraints which allocates scheduling of thermal generators in energy and reserve markets with no obligation to load and reserve satisfaction. The quality of the solution is important in deciding the commitment status and there by affecting profit incurred by GENCO/IPPs. This paper proposes a binary coded fireworks algorithm through mimicking spectacular display of glorious fireworks explosion in sky. In deregulated market GENCO/IPP has the freedom to schedule its generators in one or more market(s) based on the profit. The proposed algorithm is tested on thermal unit system for different participation scenarios namely with and without reserve market participation. Results demonstrate the superiority of the proposed algorithm in solving PBUC compared to some existing benchmark algorithms in terms of profit and number of iterations.     

Security-constrained optimal generation scheduling for GENCOs

This paper presents an approach for maximizing a GENCO's profit in a constrained power market. The proposed approach considers the Interior Point Method (IPM) and Benders decomposition for solving the security-constrained optimal generation scheduling (SC-GS) problem. The master problem represents the economic dispatch problem for a GENCO which intends to optimize its profit. The formulation of the master problem does not bear any transmission network constraints. The subproblem will be used by the same GENCO to check the viability of its proposed bidding strategy in the presence of transmission network constraints. In this case if the subproblem does not yield a certain level of financial return for the GENCO or if the subproblem results in an infeasible solution of the GENCO's proposed bidding strategy, the GENCO will modify its proposed solution according to the Benders cuts that stem out of the subproblem. The study shows a more flexible scheduling paradigm for a GENCO in a competitive arena. The proposed approach proves practical for modeling the impact of transmission congestion on a GENCO's expected profit in a competitive environment.     

Monte Carlo based unit commitment procedures for the deregulated market environment

The unit commitment problem, originally conceived in the framework of short term operation of vertically integrated utilities, needs a thorough re-examination in the light of the ongoing transition towards the open electricity market environment. In this work the problem is re-formulated to adapt unit commitment to the viewpoint of a generation company (GENCO) which is no longer bound to satisfy its load, but is willing to maximize its profits. Moreover, with reference to the present day situation in many countries, the presence of a GENCO (the former monopolist) which is in the position of exerting the market power, requires a careful analysis to be carried out considering the different perspectives of a price taker and of the price maker GENCO. Unit commitment is thus shown to lead to a couple of distinct, yet slightly different problems. The unavoidable uncertainties in load profile and price behaviour over the time period of interest are also taken into account by means of a Monte Carlo simulation. Both the forecasted loads and prices are handled as random variables with a normal multivariate distribution. The correlation between the random input variables corresponding to successive hours of the day was considered by carrying out a statistical analysis of actual load and price data. The whole procedure was tested making use of reasonable approximations of the actual data of the thermal generation units available to come actual GENCOs operating in Italy.     

Market Clearing and Settlement Using Participant Based Distributed Slack Optimal Power Flow Model for a Double Sided Electricity Auction Market –Part I

AC and DC OPF models are widely used in the industry for market clearing and settlement of primary electricity market. Research works available in literature have used locational marginal price to price electricity. But this research work by using Participant Based Distributed Slack Power Flow and a unique delivery/withdrawal point for energy called “Market Center” provides a new framework for pricing the electricity. Using the Participant Based Distributed Slack Power Flow Model a Participant based Distributed Slack Non Linear Optimal Power Flow model for market clearing and settlement of primary transaction in a double sided electricity auction market is proposed in Part 1 of this paper. Part II of this paper proposes an equivalent lumped linear model for faster convergence. The optimal solution gives the optimal schedules of the individual participants. The formulae to decompose the amount payable to GENCO participant and marginal price to be received from the DISCO participant into its components are also derived which is different from all available techniques in literature which calculate bus wise nodal prices. The proposed model is tested on Radial Five bus system and PJM system for market clearing and settlement of primary electricity market.     

基于SP/A决策思想的发电公司报价决策模型及求解方法

以安全、潜力和期望(security, potential and aspiration, SP/A)风险决策理论为基础,该文对发电公司面对风险决策时应该考虑的因素进行了分析和数学描述,其中在报价方案潜力性的分析上有效地结合了经济学中机会成本理论。在此基础上,考虑发电公司自身发电计划约束,建立起一种发电公司计及风险因素的竞价决策模型,并结合矩阵实数编码遗传算法(matrix real-coded genetic algorithm, MRCGA)对该模型的优化求解进行了探讨。该文所建的竞价决策模型既考虑了自身发电计划安排,又顾及了在面对风险发电公司竞价决策时应该考虑的一些因素,因此模型比较贴近于实际的发电竞价情况。通过算例的模拟分析表明,文中所提出的基于SP/A的发电公司竞价决策模型是合理的,其求解方法也是切实可行的。     

引导电力供需长期有效均衡的容量市场设计

容量市场是维持未来电力平衡的重要交易品种,美国PJM等国外容量市场主要解决了未来容量供应可靠性和容量电量成本分离的问题,却面临未来容量预测不准确、市场难以有效均衡的问题。提出了基于供需多方互动、引入虚拟投机商的容量市场机制,通过不同市场主体之间的多方互动和投机商的投机套利行为,建立了消除不平衡预测偏差的市场校正机制,充分调动全社会的资源和智慧,引导电力供需长期有效均衡,降低市场风险。提出了容量市场和能量市场的衔接机制,以能量市场的资产利用率作为衡量容量市场中各主体中标容量有效性的度量,以激励相容的方式抑制市场主体在能量市场上动用市场力的冲动。     

Study on stochastic optimal electric power procurement strategies with uncertain market prices

The player in deregulated electricity markets can be categorized into three groups of GENCO (Generator Companies), TRANSCO (Transmission Companies), and DISCO (Distribution Companies). This research focuses on the role of Distribution Companies, which purchase electricity from the market at randomly fluctuating prices, and provide it to their customers at given fixed prices. Therefore, Distribution Companies have to take the risk stemming from price fluctuation of electricity instead of the customers. This entails the necessity of developing a certain method to make an optimal strategy for electricity procurement. In such a circumstance, this research has the purpose of proposing a mathematical model based on stochastic dynamic programming to evaluate the value of a long‐term bilateral contract for electricity trade, and also a project of combination of the bilateral contract and power generation with their own generators for procuring electric power in a deregulated market. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 156(2): 32–42, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20105     

Feasibility evaluation of on‐site generator network by cooperative game theory

An on‐site generator, such as CGS (cogeneration system), is considered to be an effective end‐use energy system in order to accomplish primary energy conservation, CO₂ emissions mitigation, and system cost reduction; these characteristics will eventually improve the complete performance of an existing energy system in the future. Considering the drawback of installing an end‐use CGS for a customer possessing small or middle‐scale floor space, however, it is difficult to achieve those distinctive features because the thermal‐electricity ratio of CGS is not always in agreement with that of customer energy demand. In order to overcome that matching deficiency, it is better to organize an on‐site generator network based on mutual electricity and heating transmission. But focusing on some cogenerators underlying their behaviors regarding maximizing their own profits, this on‐site network, whose situation corresponds to a grand coalition, is not necessarily established because of each cogenerator's motivation to form a partial coalition and acquire its own profit as much as possible. In this paper, we attempt to analyze the optimal operation of an on‐site generator network and identify by applying the nucleolus of cooperative game theory the optimal benefit allocation strategy in order for the cogenerators to construct the network. Regarding the installation site of this network, the center of Tokyo city is assumed; the locational information includes floor space and so forth through a GIS (geographic information system) database. The results from the nucleolus suggest that all districts should impartially obtain benefit from organizing the network for the purpose of jointly attaining system total cost reduction. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 150(4): 23–35, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20052     

Coordinated preventive maintenance scheduling of GENCO and TRANSCO in restructured power systems

Preventive maintenance of generating units and lines, in a competitive electric energy environment is proposed. Inclusion of transmission constraints and forced outage rates, over a specified operational period is considered. For generator maintenance the objective of the ISO is to maintain adequate level of reliability throughout the operational period, for which Bender’s decomposition technique is used. The objective of the GENCO is to maximize profit or to minimize loss in profit, for which transmission constrained price based unit commitment (TCPBUC), based on Lagrangian relaxation method is used. Bender’s decomposition technique is used for line maintenance, with adequate level of reliability. A coordinating technique using penalty factors is incorporated to obtain convergence of the conflicting objectives. The transmission constraints are modeled using dc sensitivity factors. Detailed case studies of six-bus systems and IEEE RTS system are presented and discussed.     

多虚拟电厂参与日前电力市场的鲁棒竞标博弈方法EI北大核心CSCD

针对风电出力的不确定性和多元决策主体间的复杂博弈关系对虚拟电厂(VPP)参与日前电力市场的竞标方案的影响,提出了一种基于非合作博弈理论和鲁棒优化思想的多VPP参与日前市场的竞标博弈方法。设计了多VPP同时参与能量市场和调峰市场的非合作博弈框架和相应的交易流程。建立了各VPP在其余竞标主体报价方案的基础上,聚合多种分布式能源参与市场交易的非合作博弈竞标模型。计及风电出力不确定性对VPP运营的影响,通过强对偶理论和鲁棒优化方法将确定性竞标模型扩展为鲁棒优化模型,并在模型中引入了鲁棒调节系数来灵活调整VPP竞标方案的保守性。通过重复执行多轮竞标博弈的求解策略,直至各市场主体均不能从单方面改变投标方案中获利后,确定各VPP在日前市场中的综合出清方案。算例分析表明,所提方法给出了VPP在能量市场和调峰市场的投标优化方案,可为VPP最优参与电力市场多类型交易产品提供参考。     

Transmission access and pricing with multiple separate energyforward markets

California's congestion management protocols provide comparable access and prices to all users of the transmission system (power exchange and bilateral contract parties). The users implicitly bid for capacity on major transmission paths between zones. The independent system operator (ISO) allocates the available transmission capacity on these paths so that it maximizes the value of this capacity as measured by the users' bids. Everyone scheduling flow on a congested path is charged the marginal-cost-based price for using the path. The ISO keeps each party's portfolio of generation and load individually in balance when adjusting schedules to relieve congestion on interzonal paths. By keeping the portfolios of the different parties separate, the ISO clears its transmission market without arranging energy trades between parties. Parties are responsible for arranging their own trades. The ISO does not become involved in the energy forward markets     

面向能源互联网的多能源局域网两层功率优化分配

针对面向能源互联网的多能源局域网运行调度中的实时功率分配问题,提出一种基于多智能体两层一致性理论的多能源局域网实时动态功率分配策略。将能源互联网划分为若干个能源局域网,同时以各能源局域网和能源局域网内各分布式电源的增量成本作为一致性状态变量设计一致性功率分配算法,使得各能源局域网根据自身情况承担能源互联网系统的功率不平衡量,进一步使得各分布式电源根据自身情况承担能源局域网的功率不平衡量,从而达到降低系统发电成本的目的。该算法通过相邻智能体之间的信息交互,减少了数据通信量,并且能够很好地应对能源互联网和能源局域网拓扑结构的变化。仿真结果验证了所提方法的有效性和可行性。     

A study of basic bidding strategy in clearing pricing auctions

This paper models bidding behaviors of suppliers in electricity auction markets under clearing pricing rule and with some simplified bidding assumptions. Optimal bidding strategy of suppliers is derived by solving a set of differential equations that specify the necessary conditions for bidders to maximize their expected payoffs. The derived result indicates that bidders have incentives to mark up their bids above their costs of production. The amount of markup depends on the probability of winning below and on the margin that are computed from the cost distribution of all suppliers, market demand, and the number of suppliers participating in the auction     

Strategic bidding for electricity supply in a day-ahead energy market

The problem of building optimal bidding strategies for competitive suppliers in a day-ahead energy market is addressed in this paper. It is assumed that each supplier bids 24 linear energy supply functions, one for each hour, into the day-ahead energy market, and the market is cleared separately and simultaneously for all the delivery hours. Each supplier makes decisions on unit commitment and chooses the coefficients in the linear energy supply functions to maximize total benefits in the schedule day, subject to expectations about how rival suppliers will bid. Two different bidding schemes, namely ‘maximum hourly-benefit bidding strategies’ and ‘minimum stable output bidding strategies’, have been suggested for each hour, and based on these two schemes an overall bidding strategy in the day-ahead market can then be developed. Stochastic optimization models are first developed to describe these two different bidding schemes and a genetic algorithm based method is then presented to develop an overall bidding strategy for the day-ahead market. A numerical example is utilized to illustrate the essential features of the method.     

Achieving renewable energies utilization target in South-East Asia: Progress,challenges, and recommendations

The South-East Asian countries together have a target to increase the component of renewable energy in their primary energy supply to 23 % by 2025. However, there is a different starting point for the individual country members based on their natural conditions and specific political and regulatory frameworks. The Association of South-East Asia Nations (ASEAN), as the regional-cooperation organization, does not have the authority to intervene in the countries’ national policy for renewable energy. It can only provide inputs to develop renewable energy. However, that can also be challenging because it does not have a portal to access each member’s development of renewable energy utilization. This study aims to observe each ASEAN member’s progress by analyzing historical data. This study also reviews some academic papers to summarize the challenges and obstacles faced by each country. The result suggests that regionally, ASEAN members still rely highly on fossil fuels, especially the total primary supply. Moreover, the share of traditional biomass is also very high. Although, data shows that its use has started to reduce as countries gradually shift to other energy options, unfortunately, mostly to fossil fuel. However, power generation has developed in a positive direction. Historical data shows an increase in renewable energy use for power generation, mainly due to the higher utilization of hydropower. Furthermore, it is strongly recommended for ASEAN to build a monitoring portal of renewable energy to track the progress, so it can provide more precise policy recommendations to its members and establish better energy cooperation between each member in the future.     

A new approach to generation scheduling in interconnected power systems using predictor-corrector proximal multiplier method

The purpose of this paper is to elaborate a new generation scheduling algorithm in the interconnected power systems. Typically, the generation scheduling problem as a mixed integer non-linear programming can be effectively solved by the generalized Benders decomposition technique which decouples an original problem into the master problem and subproblems to tremendously allow fast and accurate solutions of large-scale problems. In order to formulate efficient inter-temporal optimal power flow (OPF) subproblems, we will explore a regional decomposition framework based on predictor-corrector proximal multiplier method. In fact, this scheme can find the most economic generation schedules under the power transactions for a multi-utility system without the exchange of each utility’s own private information and major disruption to existing economic dispatch or OPF adopted by individual utilities.     

联营电力市场中需求侧的直接参与

在现有的允许需求侧竞标的日前联营市场中,每当某个时段的市场清算电价高于投标报价时,需求侧的兆瓦级购电竞标就被拒绝。由于用户不参与通过削减供电量来牟利的商业运作,因此未得到满足的用户需求只能从平衡市场中在更接近于预期用电的时段中获得。这就使用户遭受更大的不能以所希望的价格来满足其对电能的需要的风险。文章介绍了一种新的市场概念,它能在日前市场对需求侧的竞标者关闭后,以合并拍卖规则中需求移动机制的方法来降低其需求不平衡的风险。